In this paper we propose a new tool for backtesting that examines the quality of Value-at-
Risk (VaR) forecasts. To date, the most distinguished regression-based backtest, proposed …

Does commodity price volatility increase when inventories are low? We are the first ones to
document this relationship. To that aim, we estimate asymmetric volatility models for a large …

One implication of the theory of storage states that commodity price volatility should increase
when inventories are low. We document this volatility feature by estimating asymmetric …

近些年, 基于大数据分析模型的风险度量和控制方法研究变得越来越重要,
而风险度量模型的后验分析研究能够保障和检验所用分析技术在实际数据分析中的有效性 …

Recent value-at-risk (VaR) models based on historical simulation often incorporate
approaches where the volatility of the historical sample is rescaled or filtered to better reflect …

Regulatory capital requirements for market risk, also known as the Fundamental Review of
the Trading Book (FRTB), were disclosed by the Basel Committee on January 2016. This …

This paper introduces a new class of models for the Value-at-Risk (VaR) and Expected
Shortfall (ES), called the Dynamic AutoRegressive Expectiles (DARE) models. Our approach …

Value at risk is a standardized measure of downside portfolio risk, required by financial
regulators, which measures financial institution's exposition to losses. There are several …

This paper provides a complete framework to aggregate different Quantile and Expectile
models for obtaining more diversified Value-at-Risk (VaR) and Expected Shortfall (ES) …

Résumé L'accroissement du risque de marché sur les places financières a conduit les
autorités de régulation à imposer le calcul d'une mesure de risques extrêmes: la Value-at …